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RPA Implementation in Auto Insurance for improved efficiency and accuracy

Overview

The American Auto Insurance company faced the challenge of a manual and time-consuming process to apply discounts to policyholders who completed a “Cautious Driver” course. This involved handling emails from three-course vendors, processing data, looking up policies, and applying discounts. The solution was RPA implementation to fully automate the process, resulting in significant efficiency gains and reduced manual labor.

Challenges

The Americal Auto Insurance company faced multiple challenges like
  • High Volume: RPA as a service was required to process over 800 new good driver discounts daily, which otherwise required substantial manpower and increased the risk of errors.
  • System Variability: The process involved two different policy management systems, each with its own quirks and requirements, making RPA Implementation complex.
  • Data Verification: Ensuring accuracy in driver and policy data, including handling name variations, posed another significant Challenge.
  • Timeliness: The manual process was time-consuming, resulting in delays in applying discounts to policyholders.

Solutions

After RPA consulting with Accelirate, the following solutions were devised.
  • RPA Implementation: To address the RPA Challenge of manual data handling, the company implemented Robotic Process Automation (RPA) to automate the entire “Cautious Driver” discount application process. This reduced the need for manual intervention and improved accuracy.
  • Efficient Data Processing: The RPA bots were used to efficiently handle emails from multiple vendors and convert the data into a standardized format. This eliminated the RPA Challenge of dealing with varied data sources and reduced errors.
  • System-Specific Workflows: RPA as a service allowed the creation of separate workflows for the two internal systems, “Insight” and “Edge.” This flexibility addressed the RPA Challenge of dealing with system variability and ensured smooth navigation and interaction.
  • Automated Updates: The RPA bots automatically updated policyholder records and applied the appropriate discounts, eliminating the RPA Challenge of timeliness and ensuring discounts were applied promptly.

Results

After the Automation, the following results were observed.
  • Elimination of Manual Labor: The RPA Implementation resulted in a 100% reduction in manual labor, freeing up employees from repetitive tasks.
  • Faster Processing: The RPA bots completed the job 33% faster than the manual process, addressing the RPA Challenge of time-consuming operations.
  • Improved Accuracy: Automation reduced the risk of errors in data handling and policy application, mitigating the RPA Challenge of data verification.
  • Digital Transformation: By embracing RPA as a service and automating this manual task, the company underwent a digital transformation, streamlining operations and reducing labor costs.